SAN JOSE, Calif.—In today’s competitive real estate finance environment, lenders and servicers need their technology teams and products to provide solutions—period.
Tag: Innovation
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 2)
Digital and industry reimaging has provided a new, integrated product solution defined by equal parts of data sciences, technologies, and business experience. Data-as-a-Product (DaaP) represents a process and organizational mindset-shift for many within financial and mortgage services, yet when adopted, the new revenue generated and efficiencies gained, illustrates the next-gen business cycle.
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 2)
Digital and industry reimaging has provided a new, integrated product solution defined by equal parts of data sciences, technologies, and business experience. Data-as-a-Product (DaaP) represents a process and organizational mindset-shift for many within financial and mortgage services, yet when adopted, the new revenue generated and efficiencies gained, illustrates the next-gen business cycle.
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 2)
Digital and industry reimaging has provided a new, integrated product solution defined by equal parts of data sciences, technologies, and business experience. Data-as-a-Product (DaaP) represents a process and organizational mindset-shift for many within financial and mortgage services, yet when adopted, the new revenue generated and efficiencies gained, illustrates the next-gen business cycle.
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 2)
Digital and industry reimaging has provided a new, integrated product solution defined by equal parts of data sciences, technologies, and business experience. Data-as-a-Product (DaaP) represents a process and organizational mindset-shift for many within financial and mortgage services, yet when adopted, the new revenue generated and efficiencies gained, illustrates the next-gen business cycle.
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 2)
Digital and industry reimaging has provided a new, integrated product solution defined by equal parts of data sciences, technologies, and business experience. Data-as-a-Product (DaaP) represents a process and organizational mindset-shift for many within financial and mortgage services, yet when adopted, the new revenue generated and efficiencies gained, illustrates the next-gen business cycle.
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 1)
Academics, consultants, and vendors advocate for “data-driven” enterprises underpinned by augmented analytics, adaptative AI/ML, digital ethics, consumer privacy, and AI security. Yet, as the pace of innovation rises across financial markets and consumer models, the organizational capabilities of leveraging data are declining. What is wrong with this picture?
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 1)
Academics, consultants, and vendors advocate for “data-driven” enterprises underpinned by augmented analytics, adaptative AI/ML, digital ethics, consumer privacy, and AI security. Yet, as the pace of innovation rises across financial markets and consumer models, the organizational capabilities of leveraging data are declining. What is wrong with this picture?
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 1)
Academics, consultants, and vendors advocate for “data-driven” enterprises underpinned by augmented analytics, adaptative AI/ML, digital ethics, consumer privacy, and AI security. Yet, as the pace of innovation rises across financial markets and consumer models, the organizational capabilities of leveraging data are declining. What is wrong with this picture?
Mark P. Dangelo: In the ‘Year of the Rabbit,’ Data is a Slow Tortoise (Part 1)
Academics, consultants, and vendors advocate for “data-driven” enterprises underpinned by augmented analytics, adaptative AI/ML, digital ethics, consumer privacy, and AI security. Yet, as the pace of innovation rises across financial markets and consumer models, the organizational capabilities of leveraging data are declining. What is wrong with this picture?